This book provides an accessible treatment of deep learning. Simon Prince curates only the ideas he considers most important with the aim of providing a high density of critical information. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. Suitable for anyone with a basic background in applied mathematics.

<ASIN: 0262048647>

Author: Simon J. D. Prince
Publisher: MIT Press
Date: December 2023
Pages: 544
ISBN: 978-0262048644
Print: 0262048647
Kindle:
Audience: General
Level: Intermediate
Category: Artificial Intelligence

Topics include:

• Up-to-date treatment of deep learning covers cutting-edge topics not found in existing texts, such as transformers and diffusion models
• Short, focused chapters progress in complexity, easing students into difficult concepts
• Pragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of models
• Streamlined presentation separates critical ideas from background context and extraneous detail
• Minimal mathematical prerequisites, extensive illustrations, and practice problems make challenging material widely accessible
• Programming exercises offered in accompanying Python Notebooks

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